library(Seurat)
## Loading required package: SeuratObject
## Loading required package: sp
## 
## Attaching package: 'SeuratObject'
## The following objects are masked from 'package:base':
## 
##     intersect, t
library(ggplot2)
neuts = readRDS(file = "/samurlab1/Joshua/RDS_obj/neutrophil_sub.rds")
neuts@active.ident = neuts$active.ident

Mature Neutrophil scoring using features defined in Ng et.al.Science (2024) doi: 10.1126/science.adf6493

mat_neut_sig = read.table(file = "/samurlab1/Joshua/MM_scRNAseq/mature_neut_sig.txt", sep = "\t")

mat_neut_sig = as.list(mat_neut_sig)

neuts = AddModuleScore(neuts, features = mat_neut_sig, name = "mat_neut_sig")
## Warning: The following features are not present in the object: RETNLG, CCL6,
## H2-D1, FTL1, CYP4F18, IL1F9, AMICA1, IFI27L2A, STFA2L1, GM5483, not searching
## for symbol synonyms
y = RidgePlot(neuts,features = "mat_neut_sig1", cols = c("#66C2A5","#D53E4F","#3288BD","#FDAE61","#ABDDA4","#FEE08B","#80B1D3") ) 
#conserving immature to mature trajectory
order = c("CXCL8+VEGFA+mat_neut","FCGR3B+CXCR2+mat_neut","Malat1+NCF1+mat_neut","S100A8/9+MMP9+imtr_neut","S100A8+LTF+imtr_neut","LTF+CAMP+imtr_neut","Mki67+DEFA3+pre-neut")
factor(y$data$ident, levels=order)
y$data$ident <- factor(y$data$ident, levels=order)
y
## Picking joint bandwidth of 0.0132

Here are the feature plots from figure 2D, I used “#steelblue” for bone marrow and “#indianred” for focal lesions

FeaturePlot(neuts, features = "MKI67", split.by = "tissue", cols = c("gray82","steelblue4"), pt.size = .6)

FeaturePlot(neuts, features = "MKI67", split.by = "tissue", cols = c("gray82","indianred"), pt.size = .6)

FeaturePlot(neuts, features = "DEFA3", split.by = "tissue", cols = c("gray82","steelblue4"), pt.size = .6)

FeaturePlot(neuts, features = "DEFA3", split.by = "tissue", cols = c("gray82","indianred"), pt.size = .6)

FeaturePlot(neuts, features = "LTF", split.by = "tissue", cols = c("gray82","steelblue4"), pt.size = .6)

FeaturePlot(neuts, features = "LTF", split.by = "tissue", cols = c("gray82","indianred"), pt.size = .6)

FeaturePlot(neuts, features = "CAMP", split.by = "tissue", cols = c("gray82","steelblue4"), pt.size = .6)

FeaturePlot(neuts, features = "CAMP", split.by = "tissue", cols = c("gray82","indianred"), pt.size = .6)

FeaturePlot(neuts, features = "MMP9", split.by = "tissue", cols = c("gray82","steelblue4"), pt.size = .6)

FeaturePlot(neuts, features = "MMP9", split.by = "tissue", cols = c("gray82","indianred"), pt.size = .6)

FeaturePlot(neuts, features = "MALAT1", split.by = "tissue",cols = c("gray82","steelblue4"), pt.size = .6, min.cutoff = 3.5)

FeaturePlot(neuts, features = "MALAT1", split.by = "tissue", cols = c("gray82","indianred"), pt.size = .6, min.cutoff = 3.5)

FeaturePlot(neuts, features = "CXCR2", split.by = "tissue",cols = c("gray82","steelblue4"), pt.size = .6)

FeaturePlot(neuts, features = "CXCR2", split.by = "tissue", cols = c("gray82","indianred"), pt.size = .6)

FeaturePlot(neuts, features = "CXCL8", split.by = "tissue",cols = c("gray82","steelblue4"), pt.size = .6)

FeaturePlot(neuts, features = "CXCL8", split.by = "tissue", cols = c("gray82","indianred"), pt.size = .6)

Violin plots from figure 2E. Printed below are those found enriched in BM

y = VlnPlot(neuts, features = "CLEC12A", split.by = "tissue" ,split.plot = TRUE, pt.size = 0, cols = c("steelblue","indianred"))
## The default behaviour of split.by has changed.
## Separate violin plots are now plotted side-by-side.
## To restore the old behaviour of a single split violin,
## set split.plot = TRUE.
##       
## This message will be shown once per session.
order = c("Mki67+DEFA3+pre-neut","S100A8+LTF+imtr_neut","LTF+CAMP+imtr_neut","S100A8/9+MMP9+imtr_neut","Malat1+NCF1+mat_neut","FCGR3B+CXCR2+mat_neut","CXCL8+VEGFA+mat_neut")
factor(y$data$ident, levels=order)
y$data$ident <- factor(y$data$ident, levels=order)
y

y = VlnPlot(neuts, features = "MMP8", split.by = "tissue" ,split.plot = TRUE, pt.size = 0, cols = c("steelblue","indianred"))

order = c("Mki67+DEFA3+pre-neut","S100A8+LTF+imtr_neut","LTF+CAMP+imtr_neut","S100A8/9+MMP9+imtr_neut","Malat1+NCF1+mat_neut","FCGR3B+CXCR2+mat_neut","CXCL8+VEGFA+mat_neut")
factor(y$data$ident, levels=order)
y$data$ident <- factor(y$data$ident, levels=order)
y

y = VlnPlot(neuts, features = "IL4R", split.by = "tissue" ,split.plot = TRUE, pt.size = 0, cols = c("steelblue","indianred"))

order = c("Mki67+DEFA3+pre-neut","S100A8+LTF+imtr_neut","LTF+CAMP+imtr_neut","S100A8/9+MMP9+imtr_neut","Malat1+NCF1+mat_neut","FCGR3B+CXCR2+mat_neut","CXCL8+VEGFA+mat_neut")
factor(y$data$ident, levels=order)
y$data$ident <- factor(y$data$ident, levels=order)
y

y = VlnPlot(neuts, features = "MMP9", split.by = "tissue" ,split.plot = TRUE, pt.size = 0, cols = c("steelblue","indianred"))

order = c("Mki67+DEFA3+pre-neut","S100A8+LTF+imtr_neut","LTF+CAMP+imtr_neut","S100A8/9+MMP9+imtr_neut","Malat1+NCF1+mat_neut","FCGR3B+CXCR2+mat_neut","CXCL8+VEGFA+mat_neut")
factor(y$data$ident, levels=order)
y$data$ident <- factor(y$data$ident, levels=order)
y

y = VlnPlot(neuts, features = "S100A12", split.by = "tissue" ,split.plot = TRUE, pt.size = 0, cols = c("steelblue","indianred"))

order = c("Mki67+DEFA3+pre-neut","S100A8+LTF+imtr_neut","LTF+CAMP+imtr_neut","S100A8/9+MMP9+imtr_neut","Malat1+NCF1+mat_neut","FCGR3B+CXCR2+mat_neut","CXCL8+VEGFA+mat_neut")
factor(y$data$ident, levels=order)
y$data$ident <- factor(y$data$ident, levels=order)
y

printed below are the features found enriched in mature neutrophils from focL lesions.

x = VlnPlot(neuts, features = "CXCL8", split.by = "tissue" ,split.plot = TRUE, pt.size = 0, cols = c("steelblue","indianred"))

order = c("Mki67+DEFA3+pre-neut","LTF+CAMP+imtr_neut","S100A8+LTF+imtr_neut","S100A8/9+MMP9+imtr_neut","Malat1+NCF1+mat_neut","FCGR3B+CXCR2+mat_neut","CXCL8+VEGFA+mat_neut")
factor(x$data$ident, levels=order)
x$data$ident <- factor(x$data$ident, levels=order)
x

x = VlnPlot(neuts, features = "IER3", split.by = "tissue" ,split.plot = TRUE, pt.size = 0, cols = c("steelblue","indianred"))

order = c("Mki67+DEFA3+pre-neut","LTF+CAMP+imtr_neut","S100A8+LTF+imtr_neut","S100A8/9+MMP9+imtr_neut","Malat1+NCF1+mat_neut","FCGR3B+CXCR2+mat_neut","CXCL8+VEGFA+mat_neut")
factor(x$data$ident, levels=order)
x$data$ident <- factor(x$data$ident, levels=order)
x

x = VlnPlot(neuts, features = "VEGFA", split.by = "tissue" ,split.plot = TRUE, pt.size = 0, cols = c("steelblue","indianred"))

order = c("Mki67+DEFA3+pre-neut","LTF+CAMP+imtr_neut","S100A8+LTF+imtr_neut","S100A8/9+MMP9+imtr_neut","Malat1+NCF1+mat_neut","FCGR3B+CXCR2+mat_neut","CXCL8+VEGFA+mat_neut")
factor(x$data$ident, levels=order)
x$data$ident <- factor(x$data$ident, levels=order)
x

x = VlnPlot(neuts, features = "TPI1", split.by = "tissue" ,split.plot = TRUE, pt.size = 0, cols = c("steelblue","indianred"))

order = c("Mki67+DEFA3+pre-neut","LTF+CAMP+imtr_neut","S100A8+LTF+imtr_neut","S100A8/9+MMP9+imtr_neut","Malat1+NCF1+mat_neut","FCGR3B+CXCR2+mat_neut","CXCL8+VEGFA+mat_neut")
factor(x$data$ident, levels=order)
x$data$ident <- factor(x$data$ident, levels=order)
x